Self-position estimation accuracy verification method and self-position estimation system

ABSTRACT

A self-position estimation accuracy verification method includes a step of moving a mobile object to a first check point, a step of acquiring first check information, a step of starting a self-position estimation using the first check information as an initial value, a step of moving the mobile object to a second check point while continuing the self-position estimation, a step of acquiring second check information, and a step of calculating a deviation between a position and a posture of the mobile object on the map estimated by the self-position estimation at the second check point and a position and a posture of the mobile object on the map indicated in the second check information, and verifying the accuracy of the self-position estimation based on the deviation.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to Japanese Patent Application No.2021-012450 filed on Jan. 28, 2021, incorporated herein by reference inits entirety.

BACKGROUND 1. Technical Field

The present disclosure relates to a self-position estimation accuracyverification method of verifying the accuracy of self-positionestimation of a mobile object, and to a self-position estimation system.

2. Description of Related Art

WO 2018/061084 discloses a self-position estimation method that enhancesthe accuracy of self-position estimation by excluding target positiondata that is estimated to have many errors in terms of a relativeposition. The self-position estimation method includes detecting arelative position between a mobile object and a target present in thesurroundings of the mobile object, accumulating a position where therelative position is moved by an amount by which the mobile object ismoved as target position data, selecting the target position data basedon reliability of the relative position of the target position data withrespect to the mobile object, and checking the selected target positiondata against map information including the position information on thetarget present on a road or in the vicinity of the road, therebyestimating a self-position that is a current position of the mobileobject.

SUMMARY

In order to start self-position estimation of a mobile object, it isnecessary to provide, as initial values, a position and a posture of themobile object on a map at the start of the self-position estimation. Atthis time, when the accuracy of the initial values is low, the accuracyof the subsequent self-position estimation is lowered. At the time ofverification of the accuracy of the self-position estimation, there is apossibility that the accuracy of the initial values is sufficientlyguaranteed and ignored, and the accuracy of the self-position estimationcannot be verified.

The present disclosure provides a self-position estimation accuracyverification method and a self-position estimation system that canguarantee the accuracy of an initial value and appropriately verify theaccuracy of self-position estimation.

A self-position estimation accuracy verification method according to afirst aspect of the present disclosure is a method of verifying accuracyof self-position estimation that estimates a position and a posture of amobile object on a map. The self-position estimation accuracyverification method includes an initial step of moving the mobile objectto a first check point, a step of specifying a position and a posture ofthe mobile object positioned at the first check point on the map andacquiring first check information indicating specified information, astep of starting the self-position estimation using the first checkinformation as an initial value, a step of moving the mobile object to asecond check point while continuing the self-position estimation, a stepof specifying a position and a posture of the mobile object positionedat the second check point on the map and acquiring second checkinformation indicating the specified information, and a verificationstep of calculating a deviation between a position and a posture of themobile object on the map estimated by the self-position estimation atthe second check point and the position and the posture of the mobileobject on the map indicated in the second check information, andverifying the accuracy of the self-position estimation based on thedeviation.

Here, the check point is a point at which the position and the postureof the mobile object on the map can be specified by a computer when themobile object is positioned. Further, the first check point and thesecond check point are any two check points that are different from eachother from among a plurality of check points.

In the first aspect, the self-position estimation accuracy verificationmethod may further include, in the verification step, when the deviationis equal to or higher than a predetermined threshold value, for sets ofthe first check point and the second check point, which are the same ordifferent from each other, returning to the initial step and repeatingeach of the steps. When the deviation is equal to or higher than thepredetermined threshold value and repetition is executed for the numberof times equal to or higher than a predetermined number of times, theaccuracy of the self-position estimation may be determined to belowered.

In the first aspect, in the verification step, when the deviation islower than the predetermined threshold value, the accuracy of theself-position estimation may be determined to be normal.

A self-position estimation system according to a second aspect of thepresent disclosure executes self-position estimation that estimates aposition and a posture of a mobile object on a map, and includes atleast one processor. The processor is configured to execute a positionspecifying process for specifying the position and the posture of themobile object on the map when the mobile object is positioned at any ofa plurality of check points, a self-position estimation process forexecuting the self-position estimation using the position and theposture of the mobile object on the map specified in the positionspecifying process as initial values, and an estimation accuracyverification process for verifying accuracy of the self-positionestimation in the self-position estimation process. Further, in theestimation accuracy verification process, the processor is configured tocalculate a deviation between a position and a posture of the mobileobject on the map indicated by estimation accuracy verificationinformation and a position and a posture of the mobile object indicatedby second check information on the map, and verify the accuracy of theself-position estimation based on the deviation.

Here, a first check point and a second check point are any two checkpoints that are different from each other from among the plurality ofcheck points. First check information is information on the position andthe posture of the mobile object on the map specified in the positionspecifying process when the mobile object is positioned at the firstcheck point. The second check information is information on the positionand the posture of the mobile object on the map specified in theposition specifying process when the mobile object is positioned at thesecond check point. The estimation accuracy verification information isinformation on a position and a posture of the mobile object on the mapestimated in the self-position estimation process when the mobile objectis moved to the second check point after the self-position estimation isstarted using the first check information as the initial value in theself-position estimation process when the mobile object is positioned atthe first check point.

In the second aspect, the estimation accuracy verification informationand the second check information may be sequentially given for each of aplurality of the same or different sets of the first check point and thesecond check point. Then, in the estimation accuracy verificationprocess, the processor may sequentially determine, for the sequentiallygiven estimation accuracy verification information and second checkinformation, whether the deviation is lower than, or equal to or higherthan a predetermined threshold value, and determine, upon determiningthat the deviation is equal to or higher than the threshold value forthe number of times equal to or higher than a predetermined number oftimes, that the accuracy of the self-position estimation is lowered.

In the second aspect, upon determining that the deviation is lower thanthe predetermined threshold value, the processor may determine that theaccuracy of the self-position estimation is normal.

In the second aspect, the mobile object may include a positionspecifying external sensor. The position specifying external sensor maybe a sensor configured to detect information for specifying the positionand the posture of the mobile object on the map.

In the second aspect, the self-position estimation system may include aposition specifying device. The position specifying device may be anexternal device configured to specify the position and the posture ofthe mobile object. The position specifying device may be installed ateach of the check points.

According to the present disclosure, when the mobile object ispositioned at the first check point, the self-position estimation isstarted using the first check information as the initial value. Then,after moving the mobile object to the second check point whilecontinuing the self-position estimation, the accuracy of theself-position estimation is verified based on the deviation between theestimation accuracy verification information and the second checkinformation. As such, it is possible to guarantee the accuracy of theinitial values of the self-position estimation, and appropriately verifythe accuracy of the self-position estimation.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, advantages, and technical and industrial significance ofexemplary embodiments of the disclosure will be described below withreference to the accompanying drawings, in which like signs denote likeelements, and wherein:

FIG. 1 is a block diagram used for describing a configuration of avehicle system according to a first embodiment;

FIG. 2 is a block diagram used for describing a self-position estimationsystem implemented by the vehicle system according to the presentembodiment;

FIG. 3 is a conceptual diagram illustrating an example of a method ofspecifying a position of a vehicle in the vehicle system according tothe first embodiment;

FIG. 4 is a conceptual diagram illustrating another example of themethod of specifying the position of the vehicle in the vehicle systemaccording to the first embodiment;

FIG. 5 is a conceptual diagram illustrating still another example of themethod of specifying the position of the vehicle in the vehicle systemaccording to the first embodiment;

FIG. 6 is a conceptual diagram used for describing an overview of aself-position estimation accuracy verification method according to thepresent embodiment;

FIG. 7 is a flowchart illustrating procedures of the self-positionestimation accuracy verification method according to the presentembodiment;

FIG. 8 is a block diagram used for describing a configuration of avehicle system according to a second embodiment;

FIG. 9 is a conceptual diagram illustrating an example of a method ofspecifying a position of a vehicle by a position specifying deviceillustrated in FIG. 8; and

FIG. 10 is a conceptual diagram illustrating another example of themethod of specifying the position of the vehicle by the positionspecifying device illustrated in FIG. 8.

DETAILED DESCRIPTION OF EMBODIMENTS

Hereinafter, embodiments of the present disclosure will be describedwith reference to the drawings. However, when numbers, such as aquantity, amount, range, and the like, of each element are referred toin the embodiments described below, the present disclosure is notlimited to the described numbers unless they are explicitly stated orthe number is clearly specified in principle. Further, structures, andthe like, described in the embodiments below are not necessarily to thepresent disclosure unless they are explicitly stated or clearlyspecified in principle. In each drawing, the same or corresponding partsare denoted by the same reference signs, and the duplicated descriptionthereof will be appropriately simplified or omitted.

A self-position estimation accuracy verification method and aself-position estimation system described in the present embodimentrelate to self-position estimation of a mobile object, such as a vehicleor a mobile robot. In particular, the present disclosure relates to theself-position estimation that gives a position and a posture of a mobileobject on a map, which are used by the mobile object that autonomouslytravels when executing an autonomous traveling control. Hereinbelow, atarget mobile object will be described as a vehicle that autonomouslytravels.

1. First Embodiment

1-1. Configuration of Vehicle System

FIG. 1 is a block diagram used for describing a configuration of avehicle system 10 according to a first embodiment. A vehicle system 10according to the first embodiment includes a vehicle 100 and a storagedevice DB.

The vehicle 100 is an autonomously driving vehicle that can autonomouslytravel. The vehicle 100 includes a sensor system 110, an HMI device 120,a communication device 130, a control device 140, and an actuator system150. The control device 140 constitutes a network so as to be capable oftransferring information with each of the sensor system 110, the HMIdevice 120, the communication device 130, and the actuator system 150.Typically, the network is an in-vehicle network in which they areelectrically connected to each other via a wire harness.

The sensor system 110 indicates a system of sensors that are provided inthe vehicle 100, and detect and output various pieces of informationnecessary for controlling the vehicle 100. The sensor system 110includes an internal sensor INS, an external sensor OSS, and a positionspecifying external sensor PTS.

The internal sensor INS detects information inside the vehicle 100, suchas a traveling state. Examples of the internal sensor INS include awheel speed sensor that detects speed of the vehicle 100, anacceleration sensor that detects acceleration of the vehicle 100, and anangular velocity sensor that detects a yaw rate of the vehicle 100.

The external sensor OSS detects information on the outside of thevehicle 100, such as the surrounding environment (a vehicle lane, anobstacle, a preceding vehicle, and the like). Examples thereof include amillimeter-wave radar, a sensor camera, and Light Detection and Ranging(LiDAR).

The position specifying external sensor PTS detects information forspecifying (hereinafter, also referred to as “position specifying”) aposition and a posture of the vehicle 100 on a map. The positionspecifying external sensor PTS is an appropriate sensor according to amethod of specifying the position of the vehicle 100. The method ofspecifying the position of the vehicle 100 will be described below.Here, the position specifying external sensor PTS may be the same as theexternal sensor OSS. In this case, the position of the vehicle 100 isspecified based on information of the external sensor OSS.

The HMI device 120 gives various pieces of information (operationinformation) to the control device 140 by an operation of an operator ofthe vehicle 100 and the like, and has a function of notifying theoperator and the like of information (processing information) onprocessing executed by the control device 140. Examples of the HMIdevice 120 include a switch, a touch panel display, an automobile meter,or a combination thereof.

The communication device 130 transmits/receives various pieces ofinformation (communication information) by communicating with anexternal device of the vehicle 100. The communication device 130includes, for example, a device that is connected to a network, such asthe Internet, and transmits/receives information to/from a device on thenetwork, a device that executes inter-vehicle communication orroad-to-vehicle communication, a Global Positioning System (GPS)receiver, or a system of devices including the above devices. Thecommunication device 130 is configured so as to be capable of acquiringinformation from at least a storage device DB described below. Examplesof the information acquired by the control device 140 via thecommunication device 130 include map information, position informationon a map using the GPS, and road traffic information.

Based on the acquired information, the control device 140 executesprocessing for controlling the vehicle 100 and generates a controlsignal. Then, the control device 140 outputs the control signal to theactuator system 150. The control device 140 is typically an electroniccontrol unit (ECU) that includes a memory and a processor.Alternatively, the control device 140 may be an external device of thevehicle 100. The memory includes a random access memory (RAM) thattemporarily stores data and a read-only memory (ROM) that stores aprogram that can be executed by the processor or various pieces of dataassociated with the program. The information acquired by the controldevice 140 is stored in the memory. The processor reads the program fromthe memory and executes processing according to the program based on thevarious pieces of data read from the memory.

The control device 140 includes a position specifying processing unitPTU, a self-position estimation processing unit LCU, an estimationaccuracy verification processing unit EVU, and an autonomous travelingcontrol processing unit ADU.

When the vehicle 100 is positioned at any of a plurality of specificpoints (hereinafter, also referred to as “check points”), the positionspecifying processing unit PTU executes processing for specifying theposition of the vehicle 100 based on detection information by theposition specifying external sensor PTS and the map information byposition specifying map data PTD that is described below, and calculatesthe position and the posture (hereinafter, also referred to as “checkinformation”) of the specified vehicle 100 on the map. In other words,the check point is a point at which the position specifying processingunit PTU can specify the position of the vehicle 100 when the vehicle100 is positioned. The position specifying processing unit PTU executesappropriate processing according to the method of specifying theposition of the vehicle 100. The method of specifying the position ofthe vehicle 100 will be described below.

Here, as the position and the posture of the vehicle 100 on the mapgiven as the check information, the same information as the result ofthe self-position estimation by the self-position estimation processingunit LCU is given. For example, as the result of the self-positionestimation by the self-position estimation processing unit LCU, theposition of the vehicle 100 on the map is given as two-dimensionalcoordinates (xe,ye) and the posture of the vehicle 100 is given as a yawangle θe. At this time, the position specifying processing unit PTUcalculates the check information that gives the position of the vehicle100 on the map as the two-dimensional coordinates (x,y) and the postureof the vehicle 100 as the yaw angle θ.

The self-position estimation processing unit LCU executes processing forself-position estimation of the vehicle 100 based on the detectioninformation by the internal sensor INS and the external sensor OSS andthe map information by traveling control map data RND that is describedbelow, and outputs the result of the self-position estimation.Typically, the self-position estimation processing unit LCU starts theprocessing using the already-known position and posture of the vehicle100 on the map as the initial values, and estimates the position and theposture of the vehicle 100 on the map every moment from a movementamount of the vehicle 100 and a positional relationship between thevehicle 100 and the surrounding environment. The movement amount of thevehicle 100 is calculated based on the detection information by theinternal sensor INS. The positional relationship between the vehicle 100and the surrounding environment is calculated based on the detectioninformation by the external sensor OSS and the map information by thetraveling control map data RND.

Here, the self-position estimation processing unit LCU according to thepresent embodiment uses the check information calculated by the positionspecifying processing unit PTU as the initial values. Further, thedegree of freedom of the position and the posture of the vehicle 100 onthe map given as the result of the self-position estimation by theself-position estimation processing unit LCU is not particularlylimited. For example, the position of the vehicle 100 on the map may begiven as two-dimensional coordinates (xe,ye), and the posture of thevehicle 100 may be given as a yaw angle θe, or each of the position andthe posture of the vehicle 100 on the map may be given as the threedegrees of freedom.

When executing the self-position estimation, the self-positionestimation processing unit LCU may create an environment map. In otherwords, the self-position estimation processing unit LCU may executeprocessing for simultaneous localization and mapping (SLAM). In thiscase, the self-position estimation may be executed based on the mapinformation by the created environment map. Examples of the environmentmap include point group data detected by the LiDAR. Further, the createdenvironment map may be stored in the memory of the control device 140 orstored as the traveling control map data RND in the storage device DBvia the communication device 130.

The estimation accuracy verification processing unit EVU verifies theaccuracy of the self-position estimation executed by the self-positionestimation processing unit LCU. The estimation accuracy verificationprocessing unit EVU verifies the accuracy of the self-positionestimation executed by the self-position estimation processing unit LCUbased on a deviation between the check information calculated by theposition specifying processing unit PTU and the self-position estimationresult of the vehicle 100 by the self-position estimation processingunit LCU. Details of the processing executed by the estimation accuracyverification processing unit EVU will be described below.

The autonomous traveling control processing unit ADU executes processingfor autonomous traveling of the vehicle 100 and generates a controlsignal for the autonomous traveling. Typically, the autonomous travelingcontrol processing unit ADU sets a traveling plan to a destination (aroute on the map to the destination, an arrival time, and the like) andgenerates a traveling route based on the traveling plan and the acquiredinformation. Then, the autonomous traveling control processing unit ADUgenerates the control signals for acceleration, braking, and steeringsuch that the vehicle 100 travels along the traveling route. Here, theinformation based on when the traveling route is generated includes theself-position estimation result of the vehicle 100 by the self-positionestimation processing unit LCU.

The control device 140 may execute other processing for controlling thevehicle 100. Each of the position specifying processing unit PTU, theself-position estimation processing unit LCU, the estimation accuracyverification processing unit EVU, the autonomous traveling controlprocessing unit ADU, or any other part that executes the processing forcontrolling may be given as a part of one program, or given as aseparate program for each process or for each group of processes andexecuted by a separate processor. Alternatively, each process or a groupof processes may be executed by a separate ECU. In this case, thecontrol device 140 is a system that consists of a plurality of ECUs, andeach of the ECUs is configured so as to be capable of transferringinformation to each other such that necessary information can beacquired when executing a process.

The actuator system 150 indicates a system of actuators that operateaccording to a control signal given from the control device 140. Theactuator system 150 includes, for example, an actuator that drives anengine (an internal combustion engine, an electric motor, or a hybridthereof, and the like), an actuator that drives a brake mechanismprovided in the vehicle 100, and an actuator that drives a steeringmechanism of the vehicle 100. Each actuator included in the actuatorsystem 150 operates according to the control signal, and thus variouscontrols of the vehicle 100 by the control device 140 are implemented.

The storage device DB stores various pieces of data and outputsinformation on the stored data. Typically, it is a database serverconfigured on the network. However, it may also be virtually configured.The traveling control map data RND and the position specifying map dataPTD are stored in the storage device DB.

The traveling control map data RND is a collection of map information ofan object on earth, and is referred to when executing the self-positionestimation, the autonomous traveling control, or other travelingcontrols. The map information of the object includes at leastinformation of a position of the object on the map. Here, the object mayinclude a feature point representing a white line or the like, or adetection point by the LiDAR. The traveling control map data RND istypically point group data or highly accurate three-dimensional mapdata. Alternatively, it may include information of the environment mapcreated by the self-position estimation processing unit LCU.

The position specifying map data PTD indicates map information forspecifying the position of the vehicle 100, and includes map informationreferred to when the position is specified. As the position specifyingmap data PTD, appropriate data according to the method of specifying theposition of the vehicle 100 is given. The method of specifying theposition of the vehicle 100 will be described below. Here, the positionspecifying map data PTD may be the same as the traveling control mapdata RND. In this case, for specifying the position of the vehicle 100,the map information by the traveling control map data RND is referredto.

The position specifying map data PTD and the traveling control map dataRND may be stored in the memory of the control device 140. In this case,the position specifying processing unit PTU, the self-positionestimation processing unit LCU, and the autonomous traveling controlprocessing unit ADU refer to the map information by the travelingcontrol map data RND or the position specifying map data PTD stored inthe memory of the control device 140.

1-2. Self-Position Estimation System

FIG. 2 is a block diagram used for describing the self-positionestimation system LCS implemented by the vehicle system 10 according tothe first embodiment. FIG. 2 illustrates transfer of the informationwhen the self-position estimation and the verification of the accuracyof self-position estimation are executed. However, arrows represented bydash-dot-dash lines indicate the transfer of the information that isgenerated only when the verification of the accuracy of self-positionestimation is executed. Further, in FIG. 2, parts that mediate thetransfer of the information are omitted. For example, the communicationdevice 130 is not shown.

The position specifying processing unit PTU calculates the checkinformation of the vehicle 100 based on the detection information by theposition specifying external sensor PTS and the map information by theposition specifying map data PTD. Then, the position specifyingprocessing unit PTU transfers the calculated check information to theself-position estimation processing unit LCU. When the verification ofthe accuracy of self-position estimation is executed, the positionspecifying processing unit PTU further transfers the calculated checkinformation to the estimation accuracy verification processing unit EVU.

The self-position estimation processing unit LCU estimates theself-position of the vehicle 100 using the check information acquiredfrom the position specifying external sensor PTS as the initial valuebased on the detection information by the internal sensor INS, thedetection information by the external sensor OSS, and the mapinformation by the traveling control map data RND. Then, theself-position estimation processing unit LCU outputs a result of theself-position estimation. When the verification of the accuracy ofself-position estimation is executed, the self-position estimationprocessing unit LCU transfers the result of self-position estimation tothe estimation accuracy verification processing unit EVU.

When executing the verification of the accuracy of self-positionestimation, based on the deviation between the check informationacquired from the position specifying processing unit PTU and theself-position estimation result acquired from the self-positionestimation processing unit LCU, the estimation accuracy verificationprocessing unit EVU verifies the accuracy of the self-positionestimation, which is executed by the self-position estimation processingunit LCU. Then, the estimation accuracy verification processing unit EVUoutputs the verification result of the accuracy of self-positionestimation.

1-3. Method of Specifying Position of Vehicle

The vehicle system 10 according to the first embodiment specifies(position specifying) the position and the posture of the vehicle 100 onthe map when the vehicle 100 is positioned at any of the plurality ofcheck points. Hereinafter, the method of specifying the position of thevehicle 100 in the vehicle system 10 according to the first embodimentwill be described.

FIG. 3 is a conceptual diagram illustrating one example of the method ofspecifying the position of the vehicle 100. In the example illustratedin FIG. 3, two objects FT1, FT2 are installed at a check point CP. Inthis example, the position specifying map data PTD is given so as toinclude information on positions of objects on the map installed at thecheck point CP. In other words, the position specifying map data PTDincludes information on the positions of the two objects FT1, FT2 on themap. Therefore, the position specifying external sensor PTS detects arelative position between the vehicle 100 and the objects FT1, FT2,thereby specifying the position of the vehicle 100.

In other words, the position specifying processing unit PTU calculatesthe check information of the vehicle 100 based on the information on theposition of the objects FT1, FT2 on the map acquired from the positionspecifying map data PTD and the information on the relative positionbetween the vehicle 100 and the objects FT1, FT2 acquired from theposition specifying external sensor PTS. In this case, examples of theposition specifying external sensor PTS include a millimeter-wave radar,a sensor camera, LiDAR, or a combination thereof.

The check point CP may include three or more objects. Further, eachobject included in the check point CP can be distinguished from eachother by the position specifying external sensor PTS, and is configuredsuch that its corresponding position information can be appropriatelyacquired from the position specifying map data PTD. For example, eachobject is configured to have a shape, color, or a pattern that can bedistinguished from each other by image recognition of a sensor camera orthe LiDAR. Alternatively, each object may be provided with an opticalreflector (for example, a reflector having a different reflectance formillimeter-wave radio waves) and the like that can be distinguished fromeach other by a millimeter-wave radar.

FIG. 4 is a conceptual diagram illustrating another example of themethod of specifying the position of the vehicle 100. In the exampleillustrated in FIG. 4, parking lines FR that define a parking place ofthe vehicle 100 are marked and an object FT is installed in the vicinityof the parking lines FR at the check point CP. Further, the object FT ismarked with a mark MK that can be recognized by the position specifyingexternal sensor PTS. The mark MK corresponds to information on theposition and the posture of the vehicle 100 on the map when the vehicle100 is parked along the parking lines FR. Therefore, when the vehicle100 is parked along the parking lines FR, the position specifyingexternal sensor PTS acquires the map information corresponding to themark MK by recognizing the mark MK. As such, it is possible to specifythe position of the vehicle 100.

The mark MK is a code, such as a two-dimensional code, and specificinformation can be acquired by recognizing it. In this case, theposition specifying external sensor PTS is a reading sensorcorresponding to the mark MK, such as a code reader or the like.Further, in this case, the information directly obtained by recognizingthe mark MK may be an ID corresponding to the map information on theposition and the posture of the vehicle 100 on the map. In other words,the position of the vehicle 100 may be specified when the positionspecifying external sensor PTS acquires the ID by recognizing the markMK, and the position specifying processing unit PTU acquires, from theposition specifying map data PTD, the map information corresponding tothe acquired ID. Therefore, in this case, the position specifying mapdata PTD is data to which the map information is given for each ID.

Further, the mark MK may be a specific color or a pattern that can berecognized and distinguished by the sensor camera or LiDAR, or aspecific optical reflector that can be recognized and distinguished bythe millimeter-wave radar. In this case, the position specifyingexternal sensor PTS is the millimeter-wave radar, the sensor camera, orLiDAR, and the position of the vehicle 100 is specified in the samemanner as above.

Further, the position specifying external sensor PTS may detect arelative position between the parking lines FR and the vehicle 100, and,based on the detected relative position, the position specifyingprocessing unit PTU may correct the information on the position and theposture of the vehicle 100 on the map obtained from the mark MK. Assuch, it is possible to further enhance the accuracy of specifying theposition of the vehicle 100. In this case, the position specifyingexternal sensor PTS includes a sensor that is used for recognizing themark MK and a sensor (the sensor camera, the LiDAR, and the like) thatcan detect the relative position between the parking lines FR and thevehicle 100. However, the recognition of the mark MK and the detectionof the relative position between the parking lines FR and the vehicle100 may be executed by the same sensor.

FIG. 5 is a conceptual diagram illustrating still another example of themethod of specifying the position of the vehicle 100. In the exampleillustrated in FIG. 5, the parking lines FR that define a parking placefor the vehicle 100 are marked at the check point CP. Further, theposition specifying map data PTD includes the information on positionsand postures of the vehicle 100 on the map when the vehicle 100 isparked along the parking lines FR, for respective parking lines FRmarked at the plurality of check points.

In the example illustrated in FIG. 5, the position of the vehicle 100 isspecified while the vehicle 100 is parked along the parking lines FR.When the position is specified, the vehicle 100 detects its position onthe map using the GPS. Then, the position specifying processing unit PTUestimates that the vehicle 100 is parked at parking lines FR closest tothe position of the vehicle 100 on the map detected by the GPS, andspecifies the position of the vehicle 100. In other words, the positionspecifying processing unit PTU acquires, from the position specifyingmap data PTD, map information on the parking lines FR closest to theposition of the vehicle 100 on the map detected by the GPS, and uses theposition and the posture of the vehicle 100 on the map indicated by theacquired map information as check information of the vehicle 100.

Here, when the position specifying map data PTD does not include the mapinformation on the parking lines FR that is sufficiently close to theposition of the vehicle 100 on the map detected by the GPS, the positionspecifying processing unit PTU may determine that the position cannot bespecified. This means that, for example, the position specifying mapdata PTD can determine as above when all the deviations between theinformation on the position of the vehicle 100 on the map for therespective parking lines FR included in the position specifying map dataPTD and the position of the vehicle 100 on the map detected by the GPSare higher than a predetermined threshold value. At this time, theposition specifying processing unit PTU may notify (display, make asound, and the like) the operator, and the like, of the vehicle 100 thatthe position cannot be specified via the HMI device 120.

Further, the position specifying external sensor PTS may detect therelative position between the parking lines FR and the vehicle 100, andthe position specifying processing unit PTU may correct, based on thedetected relative position, the map information on the parking lines FRacquired from the position specifying map data PTD.

The examples of the method of specifying the position of the vehicle 100have been described above, but the position of the vehicle 100 may bespecified by other methods.

1-4. Self-Position Estimation Accuracy Verification Method

FIG. 6 is a conceptual diagram used for describing an overview of aself-position estimation accuracy verification method according to thepresent embodiment. The self-position estimation accuracy verificationmethod according to the present embodiment is a method of verifying theaccuracy of the self-position estimation of the vehicle 100, which isexecuted by the self-position estimation processing unit LCU. Theself-position estimation accuracy verification method is executed at anytwo check points that are different from each other from among theplurality of check points. FIG. 6 illustrates a first check point CP1and a second check point CP2 as the two check points.

First, the vehicle 100 is moved to the first check point CP1 (an initialstep). After the vehicle 100 is moved to the first check point CP1, theposition specifying processing unit PTU specifies the position of thevehicle 100, and acquires check information of the vehicle 100 at thefirst check point CP1 (hereinafter, also referred to as “first checkinformation”). Thereafter, the self-position estimation processing unitLCU starts the self-position estimation using the first checkinformation as the initial value.

Next, the vehicle 100 is moved to the second check point CP2 (RT) whilethe self-position estimation processing unit LCU continues theself-position estimation. Here, the vehicle 100 may be moved to thesecond check point CP2 (RT) in any manner. For example, it may be movedby the autonomous traveling control by the autonomous traveling controlprocessing unit ADU, or moved by manual driving or towing.

After the vehicle 100 is moved to the second check point CP2, theposition specifying processing unit PTU specifies the position of thevehicle 100, and acquires check information of the vehicle 100 at thesecond check point CP2 (hereinafter, also referred to as “second checkinformation”). Then, the estimation accuracy verification processingunit EVU verifies the accuracy of the self-position estimation based ona deviation between the second check information and the result of theself-position estimation (hereinafter, also referred to as “estimationaccuracy verification information”) which is executed by theself-position estimation processing unit LCU at the second check pointCP2 (a verification step).

Here, when a verification result is not given by the estimation accuracyverification processing unit EVU, the same procedures are repeated forthe same or different sets of the first check point CP1 and the secondcheck point CP2. For example, the check points designated as the firstcheck point CP1 and the second check point CP2 are switched, and thesame procedures are repeated.

FIG. 7 is a flowchart illustrating the procedures of the self-positionestimation accuracy verification method according to the presentembodiment. Details of the self-position estimation accuracyverification method according to the present embodiment will bedescribed with reference to the flowchart illustrated in FIG. 7.

In step S100 (the initial step), the vehicle 100 is moved to the firstcheck point CP1. The first check point CP1 may be any of the pluralityof check points. Further, the vehicle 100 may be moved to the firstcheck point CP1 in any manner. After step S100, the process proceeds tostep S110.

In step S110, the first check information is acquired. The positionspecifying processing unit PTU calculates the first check information.After step S110, the process proceeds to step S120.

In step S120, the self-position estimation processing unit LCU startsthe self-position estimation using the first check information as theinitial value. After step S120, the process proceeds to step S130.

In step S130, the vehicle 100 is moved to the second check point CP2while the self-position estimation processing unit LCU continues theself-position estimation. The second check point CP2 may be any of theplurality of check points as long as it is different from the firstcheck point CP1. Further, the vehicle 100 may be moved to the secondcheck point CP2 in any manner. After step S130, the process proceeds tostep S140.

In step S140, the second check information is acquired. The positionspecifying processing unit PTU calculates the second check information.After step S140, the process proceeds to step S150. Here, the estimationaccuracy verification processing unit EVU executes the procedures (theverification step) described in steps S150 to S200.

In step S150, the estimation accuracy verification processing unit EVUacquires the estimation accuracy verification information and the secondcheck information from the position specifying processing unit PTU andthe self-position estimation processing unit LCU, and calculates adeviation between the position and the posture of the vehicle 100 on themap indicated by the estimation accuracy verification information andthe position and the posture of the vehicle 100 on the map indicated bythe second check information.

Here, an example of calculating the deviation is described below. As thesecond check information, it is assumed that the position of the vehicle100 on the map is given as two-dimensional coordinates (x2,y2) and theposture of the vehicle 100 is given as a yaw angle θ2. Further, as theestimation accuracy verification information, it is assumed that theposition of the vehicle 100 on the map is given as the two-dimensionalcoordinates (xe,ye) and the posture of the vehicle 100 is given as a yawangle θe. At this time, the deviation is calculated according to thefollowing equation (1):

[Formula 1]

|x2−xe|²+|y2−ye|²+|θ2−θe|²   (1)

Similarly, the deviation may be calculated for each of the position andthe posture of the vehicle 100 on the map. After step S150, the processproceeds to step S160.

In step S160, the estimation accuracy verification processing unit EVUdetermines whether the deviation calculated in step S150 is lower than apredetermined threshold value k. Here, the threshold value k is a valuegiven to the program in advance. This is optimally and experimentallydetermined by, for example, vehicle compatibility of the vehicle 100 towhich the vehicle system 10 according to the present embodiment isapplied.

When the deviation is lower than the threshold value k (step S160: Yes),the estimation accuracy verification processing unit EVU determines thatthe accuracy of the self-position estimation executed by theself-position estimation processing unit LCU is normal (step S170), andthe process ends. On the other hand, when the deviation is equal to orhigher than the predetermined threshold value k (step S160: No), theprocess proceeds to step S180.

In step S180, the estimation accuracy verification processing unit EVUincreases the number of times that the procedures are repeated. Here,the number of times of repetition is initialized at the start of theprocedures illustrated in FIG. 7 (for example, the number of times ofrepetition is set to zero). After step S180, the process proceeds tostep S190.

In step S190, the estimation accuracy verification processing unit EVUdetermines whether the number of times of repetition is equal to orhigher than a predetermined number of times N. Here, the predeterminednumber of times N is a value given to the program in advance.

When the number of times of repetition is equal to or higher than thepredetermined number of times N (step S190: Yes), the estimationaccuracy verification processing unit EVU determines that the accuracyof the self-position estimation executed by the self-position estimationprocessing unit LCU is lowered (step S200), and the process ends. On theother hand, when the number of times of repetition is lower than thepredetermined number of times N (step S190: No), the estimation accuracyverification processing unit EVU does not give the verification result,and the process proceeds to step S210.

In step S210, the first check point CP1 and the second check point CP2are changed. For example, the check points designated as the first checkpoint CP1 and the second check point CP2 are switched. After step S210,the process returns to step S100 and the procedures are repeated. Here,the process of step S210 is not necessary. In other words, theprocedures may be repeated for the same set of the first check point andthe second check point.

As above, the self-position estimation accuracy verification method hasbeen described. Whether to start processing or a response may bedetermined according to the verification result by the self-positionaccuracy verification estimation method. For example, when theestimation accuracy verification processing unit EVU determines that theaccuracy of the self-position estimation is normal (step S170), theautonomous traveling control processing unit ADU starts the processingfor the autonomous traveling control. As another example, when theestimation accuracy verification processing unit EVU determines that theaccuracy of the self-position estimation is lowered (step S200), afailure of devices (the sensor system 110, the control device 140, theactuator system 150, and the like) for the self-position estimation isconfirmed.

Further, even when the estimation accuracy verification processing unitEVU determines the accuracy of the self-position estimation is normal(step S170), in a case where the repetition is executed at least once,whether to execute processing or a response may be determined accordingto the number of times of repetition. For example, a notification tocall attention is sent to the operator and the like via the HMI device120. Alternatively, as another example, the fact that the repetition hasbeen executed is recorded in the memory of the control device 140.

2. Second Embodiment

Hereinafter, a second embodiment will be described. Thealready-described content above will be appropriately omitted.

2-1. Configuration of Vehicle System

In the second embodiment, the position of the vehicle 100 is specifiedby an external device. FIG. 8 is a block diagram used for describing aconfiguration of a vehicle system 10 according to the second embodiment.As illustrated in FIG. 8, in the second embodiment, the sensor system110 of the vehicle 100 does not include the position specifying externalsensor PTS, and the control device 140 does not include the positionspecifying processing unit PTU. On the other hand, the vehicle system 10according to the second embodiment includes a position specifying device200.

The position specifying device 200 is an external device that specifiesthe position of the vehicle 100. The position specifying device 200 isinstalled at each of a plurality of check points CP. Alternatively, theposition specifying device 200 may be a specific device prepared whenthe position of the vehicle 100 is specified. When the vehicle 100 ispositioned at each check point, the position specifying device 200specifies the position of the vehicle 100 and calculates the checkinformation. Then, as represented by a dash-dot-dash line in FIG. 8, thecheck information of the vehicle 100 is transferred to the vehicle 100via the communication device 130. Here, communication between theposition specifying device 200 and the vehicle 100 may be in any manner.For example, the communication may be via radio waves or a network, suchas the Internet.

The check information of the vehicle 100 may be transferred to thevehicle 100 via the HMI device 120. In this case, the check informationcalculated by the position specifying device 200 is given by anoperation of the HMI device 120, and, as a result, the check informationis transferred to the control device 140 as operation information of theHMI device 120.

The position specifying device 200 includes the position specifyingexternal sensor PTS and an information processing device 240.

The position specifying external sensor PTS is an appropriate sensoraccording to a method by which the position specifying device 200specifies the position of the vehicle 100. The method by which theposition specifying device 200 specifies the position of the vehicle 100will be described below.

The information processing device 240 is typically a computer thatincludes a memory and a processor. The information processing device 240stores the position specifying map data PTD. The information processingdevice 240 also includes the position specifying processing unit PTU.The position specifying processing unit PTU calculates the checkinformation of the vehicle 100 based on the detection information by theposition specifying external sensor PTS and the map information by theposition specifying map data PTD. The position specifying processingunit PTU executes appropriate processing according to the method bywhich the position specifying device 200 specifies the position of thevehicle 100. The method by which the position specifying device 200specifies the position of the vehicle 100 will be described below.

The self-position estimation system LCS implemented by the vehiclesystem 10 according to the second embodiment is the same as thatillustrated in FIG. 2.

2-2. Method of Specifying Position of Vehicle

Hereinafter, in the vehicle system 10 according to the secondembodiment, the method by which the position specifying device 200specifies the position of the vehicle 100 will be described.

FIG. 9 is a conceptual diagram illustrating one example of the method bywhich the position specifying device 200 specifies the position of thevehicle 100. In the example illustrated in FIG. 9, the positionspecifying external sensor PTS of the position specifying device 200installed at the check point CP is illustrated. In this example, theposition specifying map data PTD is given to include information on aposition of the position specifying external sensor PTS on the map.Therefore, the position specifying external sensor PTS detects therelative position between the position specifying external sensor PTSand the vehicle 100, thereby specifying the position of the vehicle 100on the map. Further, the position specifying external sensor PTS detectsthe posture of the vehicle 100 with respect to the position specifyingexternal sensor PTS, thereby specifying the posture of the vehicle 100.

In other words, the position specifying processing unit PTU calculatesthe check information of the vehicle 100 based on the information on theposition of the position specifying external sensor PTS on the mapacquired from the position specifying map data PTD and the detectioninformation on the position specifying external sensor PTS acquired fromthe position specifying external sensor PTS. In this case, examples ofthe position specifying external sensor PTS include a millimeter-waveradar, a sensor camera, LiDAR, or a combination thereof.

Here, the vehicle 100 may be configured such that it can beappropriately detected by the position specifying external sensor PTS.For example, when the position specifying external sensor PTS includesthe millimeter-wave radar, the vehicle 100 may include the opticalreflector.

FIG. 10 is a conceptual diagram illustrating another example of themethod by which the position specifying device 200 specifies theposition of the vehicle 100. In the example illustrated in FIG. 10, theposition specifying external sensor PTS of the position specifyingdevice 200 installed at the check point CP is illustrated. Further, theparking lines FR that define the parking place of the vehicle 100 aremarked at the check point CP. In this example, the position specifyingmap data PTD is given to include information on a position of theparking lines FR on the map. Therefore, the position specifying externalsensor PTS detects the relative position between the parking lines FRand the vehicle 100, thereby specifying the position of the vehicle 100.

In other words, the position specifying processing unit PTU calculatesthe check information of the vehicle 100 based on the information on theposition of the parking lines FR on the map acquired from the positionspecifying map data PTD and information on the relative position betweenthe parking lines FR and the vehicle 100 acquired from the positionspecifying external sensor PTS. In this case, examples of the positionspecifying external sensor PTS include a millimeter-wave radar, a sensorcamera, LiDAR, or a combination thereof.

As above, the examples of the method by which the position specifyingdevice 200 specifies the position of the vehicle 100 have beendescribed, but the position specifying device 200 may specify theposition of the vehicle 100 using other methods.

2-3. Self-Position Estimation System

The self-position estimation accuracy verification method executed bythe vehicle system 10 according to the second embodiment is the same asthat described with reference to FIGS. 6 and 7 in the first embodiment.However, in the vehicle system 10 according to the second embodiment,the first check information and the second check information describedin steps S110 and S140 of the flowchart illustrated in FIG. 7 iscalculated by the position specifying device 200.

3. Effect

As described above, according to the self-position estimation accuracyverification method and the self-position estimation system LCS of thepresent embodiment, the self-position estimation is started using thefirst check information as the initial value while the vehicle 100 ispositioned at the first check point CP1. Then, after the vehicle 100 ismoved to the second check point while the self-position estimationprocessing unit LCU continues the self-position estimation, theself-position estimation processing unit LCU verifies the accuracy ofthe self-position estimation based on the deviation between theestimation accuracy verification information and the second checkinformation.

As such, the initial value of the self-position estimation is given bythe position and the posture (the first check information) of thevehicle 100 specified at any of the check points CP on the map, and thusit is possible to guarantee the accuracy of the initial values of theself-position estimation and to appropriately verify the accuracy of theself-position estimation.

Further, when the deviation is equal to or higher than the predeterminedthreshold value k, the accuracy of the self-position estimation isrepeatedly verified, and when the number of times of repetition is equalto or higher than the predetermined number of times N, it is determinedthat the accuracy of the self-position estimation is lowered. As such,it is possible to reduce a determination error due to the stochasticfluctuations of the result of the self-position estimation.

In the present embodiment, the self-position estimation accuracyverification method and the self-position estimation system LCS havebeen described using the vehicle 100 as a target, but the sameadvantageous effect can be obtained by suitably employing them to othermobile objects.

What is claimed is:
 1. A self-position estimation accuracy verificationmethod of verifying accuracy of self-position estimation that estimatesa position and a posture of a mobile object on a map, a check pointbeing a point at which the position and the posture of the mobile objecton the map is specifiable by a computer when the mobile object ispositioned, and a first check point and a second check point being anytwo check points that are different from each other from among aplurality of check points, the self-position estimation accuracyverification method comprising: an initial step of moving the mobileobject to the first check point; a step of specifying a position and aposture of the mobile object positioned at the first check point on themap and acquiring first check information indicating specifiedinformation; a step of starting the self-position estimation using thefirst check information as an initial value; a step of moving the mobileobject to the second check point while continuing the self-positionestimation; a step of specifying a position and a posture of the mobileobject positioned at the second check point on the map and acquiringsecond check information indicating the specified information; and averification step of calculating a deviation between a position and aposture of the mobile object on the map estimated by the self-positionestimation at the second check point and the position and the posture ofthe mobile object on the map indicated in the second check information,and verifying the accuracy of the self-position estimation based on thedeviation.
 2. The self-position estimation accuracy verification methodaccording to claim 1, further comprising: in the verification step, whenthe deviation is equal to or higher than a predetermined thresholdvalue, for sets of the first check point and the second check point,which are the same or different from each other, returning to theinitial step and repeating each of the steps, wherein when the deviationis equal to or higher than the predetermined threshold value andrepetition is executed for the number of times equal to or higher than apredetermined number of times, the accuracy of the self-positionestimation is determined to be lowered.
 3. The self-position estimationaccuracy verification method according to claim 1, wherein, in theverification step, when the deviation is lower than a predeterminedthreshold value, the accuracy of the self-position estimation isdetermined to be normal.
 4. A self-position estimation system whichexecutes self-position estimation that estimates a position and aposture of a mobile object on a map, the self-position estimation systemcomprising: at least one processor configured to execute: a positionspecifying process for specifying the position and the posture of themobile object on the map when the mobile object is positioned at any ofa plurality of check points; a self-position estimation process forexecuting the self-position estimation using the position and theposture of the mobile object on the map specified in the positionspecifying process as initial values; and an estimation accuracyverification process for verifying accuracy of the self-positionestimation in the self-position estimation process, wherein: a firstcheck point and a second check point are any two check points that aredifferent from each other from among the plurality of check points;first check information is information on the position and the postureof the mobile object on the map specified in the position specifyingprocess when the mobile object is positioned at the first check point;second check information is information on the position and the postureof the mobile object on the map specified in the position specifyingprocess when the mobile object is positioned at the second check point;estimation accuracy verification information is information on aposition and a posture of the mobile object on the map estimated in theself-position estimation process when the mobile object is moved to thesecond check point after the self-position estimation is started usingthe first check information as the initial value in the self-positionestimation process when the mobile object is positioned at the firstcheck point; and in the estimation accuracy verification process, theprocessor is configured to calculate a deviation between the positionand the posture of the mobile object on the map indicated by theestimation accuracy verification information and the position and theposture of the mobile object indicated by the second check informationon the map, and to verify the accuracy of the self-position estimationbased on the deviation.
 5. The self-position estimation system accordingto claim 4, wherein: the estimation accuracy verification informationand the second check information are sequentially given for each of aplurality of the same or different sets of the first check point and thesecond check point; in the estimation accuracy verification process, theprocessor is configured to: sequentially determine, for the sequentiallygiven estimation accuracy verification information and second checkinformation, whether the deviation is lower than, or equal to or higherthan a predetermined threshold value; and determine, upon determiningthat the deviation is equal to or higher than the threshold value forthe number of times equal to or higher than a predetermined number oftimes, that the accuracy of the self-position estimation is lowered. 6.The self-position estimation system according to claim 4, wherein, inthe estimation accuracy verification process, the processor isconfigured to determine, upon determining that the deviation is lowerthan a predetermined threshold value, that the accuracy of theself-position estimation is normal.
 7. The self-position estimationsystem according to claim 4, wherein: the mobile object includes aposition specifying external sensor; and the position specifyingexternal sensor is a sensor configured to detect information forspecifying the position and the posture of the mobile object on the map.8. The self-position estimation system according to claim 4, wherein:the self-position estimation system includes a position specifyingdevice; the position specifying device is an external device configuredto specify the position and the posture of the mobile object; and theposition specifying device is installed at each of the check points.